Milde M. S. Lira

According to our database1, Milde M. S. Lira authored at least 24 papers between 2006 and 2016.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2016
Assessment of power curves in models of wind power forecasting.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015
Echo state networks, artificial neural networks and fuzzy systems models for improve short-term wind speed forecasting.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Improving reservoir based wind power forecasting with ensembles.
Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

Investigating the use of Echo State Networks for prediction of wind power generation.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence for Engineering Solutions, 2014

2013
Forecasting models of wind power in Northeastern of Brazil.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
Wind forecasting and wind power generation: Looking for the best model based on artificial intelligence.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Models Based on Neural Networks and Neuro-Fuzzy Systems for Wind Power Prediction Using Wavelet Transform as Data Preprocessing Method.
Proceedings of the Engineering Applications of Neural Networks, 2012

2011
Solving a real large scale mid-term scheduling for power plants via hybrid intelligent neural networks systems.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Short-term load forecasting for electrical regional of a distribution utility considering temperature.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010
Inflow forecasting models based on artificial intelligence.
Proceedings of the International Joint Conference on Neural Networks, 2010

Recurrent neural networks solving a real large scale mid-term scheduling for power plants.
Proceedings of the International Joint Conference on Neural Networks, 2010

A fuzzy system for detection of incipient fault in power transformers based on gas-in-oil analysis.
Proceedings of the FUZZ-IEEE 2010, 2010

2009
Application of wavelet and neural network models for wind speed and power generation forecasting in a Brazilian experimental wind park.
Proceedings of the International Joint Conference on Neural Networks, 2009

Combining Artificial Neural Network for diagnosing polluted insulators.
Proceedings of the International Joint Conference on Neural Networks, 2009

2008
Investigating the use of Reservoir Computing for forecasting the hourly wind speed in short -term.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
Combining Multiple Artificial Neural Networks Using Random Committee to Decide upon Electrical Disturbance Classification.
Proceedings of the International Joint Conference on Neural Networks, 2007

Development of an Artificial Neural Network by Genetic Algorithm to Mid-Term Load Forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2007

Boosting Algorithm to Improve a Voltage Waveform Classifier Based on Artificial Neural Network.
Proceedings of the Artificial Neural Networks, 2007

Combined Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for Improving a Short-Term Electric Load Forecasting.
Proceedings of the Artificial Neural Networks, 2007

Using Genetic Algorithm to Develop a Neural-Network-Based Load Forecasting.
Proceedings of the Artificial Neural Networks, 2007

2006
Improving Disturbance Classification by Combining Multiple Artificial Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2006

A Hybrid Intelligent System for Short and Mid-term Forecasting for the CELPE Distribution Utility.
Proceedings of the International Joint Conference on Neural Networks, 2006

Combining Artificial Neural Networks and Heuristic Rules in a Hybrid Intelligent Load Forecast System.
Proceedings of the Artificial Neural Networks, 2006

Development of a Hybrid Intelligent System for Electrical Load Forecasting.
Proceedings of the Advances in Artificial Intelligence, 2006


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